Poisson Equation in Sobolev Spaces

Size: px
Start display at page:

Download "Poisson Equation in Sobolev Spaces"

Transcription

1 Poisson Equation in Sobolev Spaces OcMountain Dayligt Time. 6, 011 Today we discuss te Poisson equation in Sobolev spaces. It s existence, uniqueness, and regularity. Weak Solution. u = f in, u = g on (1) Definition 1. u W 1, () is a weak solution of te Poisson equation if u = f, in, u= g, on () u v + f v = 0 v W 1, 0 (); u g W 1, 0 (). (3) Te weak formulation is advantageous in getting quick estimates. For example, wen g = 0, we ave u W 1, C f L (4) for some constant C. To see tis, note tat wen g = 0, u W 1, 0 can be used as a test function, wic gives u = fu f L u L. (5) Applying Poincaré inequality gives te desired estimate. Existence. Te direct metod sows te existence/uniqueness of te solution of PDEs by studying its variational formulation. We sketc tis approac by studying te Poisson equation wit zero boundary condition: u= f, u W 0 1, (). (6) We know tat any weak solution to tis problem is a minimizer of te functional I(u)= u + fu. (7) We would like to sow tat te minimizer exists. We apply te so-called direct metod : Assume f L. 1. Writing I(u) u ε u 1 f (8) 4ε and recalling te Poincaré s inequality, we see tat I(u) as finite infimum.. Let u n be suc tat I(u n ) ց inf u W0 1,I(u). We sow tat tere is a subsequence converging to some limit u W 0 1,. To see tis, note tat a uniform bound on I(u n ) implies a uniform bound on un, since I(u) u L u L f L u L C u L =( u L C) u L. (9) by Hölder s inequality and Poincaré s inequality. 3. Uniform boundedness of u n L implies tat u n is uniformly bounded in W 0 1, and tus as a weakly 1 converging subsequence, still denoted by u n. We denote te limit by u. 1. Te weak convergence is in W 1,. Recall tat a sequence {u n } in a Hilbert space H is weakly convergent wit weak limit u H if (u n,v) (u,v) for any v H. Furtermore, using compact embedding, we see tat wen u n converges to u weakly in W 1,, we can find a subsequence, still denoted u n, converging to u strongly in L, at te same time u n converges to u weakly in L. 1

2 Poisson Equation in Sobolev Spaces 4. Te convexity of te functional I(u) ten guarantees tat wic means u is a minimizer. Uniqueness. Let u, v be weak solutions to Let w =u v. Ten w is weak solution to I(u ) liminf I(u n)= nր inf u W 0 1, I(u) (10) u= f in, u = g on (11) w = 0 in, w = 0 on. (1) Note tat as w C, we cannot directly apply te maximum principle for armonic functions. However proving troug te definition of weak solution is as simple. Left as a problem. Interior Regularity. Our goal is te prove te following teorem, wic justifies te intuition tat u is twice more differentiable tan f. By interior regularity, we mean we do not deal wit boundary data, and terefore te L -norm of u is necessary in te RHS. Teorem. Let u W 1, () be a weak solution of u = f wit f L (). For any, we ave u W, ( ), and u W, ( ) C ( u L () + f L ()). (13) were te constant depends on te distance between and. Furtermore, u= f almost everywere in. Remark 3. Te difficulty in proving te teorem lies in te fact tat we ave to sow u W,. Once tis is known, te estimate is relatively easy to establis. 1. We first sow tat u L ( ) 17 δ u L () witout any extra assumptions. Let η(x) be a cut-off function defined by 1 x η(x) = 1 1 δ dist(x, ) 0 dist(x, ) δ 0 dist(x, )>δ and set te test function Some calculation yields Using Young s inequality + δ f L (). (14) (15) v = η u W 0 1, (). (16) η u + (η u) (u η)= η f u. (17) ab ε a + 1 ε b a, b R, ε > 0 (18) on te nd term on te LHS and on te RHS we ave η u 1 η u + u η + 1 δ η u + δ η f. (19) Moving te first term on te RHS to te left, we ave ( 16 u δ + 1 ) δ u + δ f. (0)

3 OcMountain Dayligt Time. 6, Note tat u = u + boundary terms. if we assume u W 3,. Tus using u as test function we obtain u L ( ) Proof. Let, wit dist(, ) δ/4, dist(, ) δ/4. Now coose η C 0 1 ( ) wit η = 1 on and η 8/δ, and set were Ten we ave Recalling We ave f L (). (1) v = η i u () i u(x)= u(x+e i) u(x) ( i u) v = i ( u) v = u ( i v) = f i v (3) f L () v L ( ). (4) v = η i u (5) ( i u) (η i u) f L () (η i u) L ( ). (6) Te terms can be expanded to obtain η ( i u) f L () (η i u) L ( ) (η i u) ( i u η) f L () (η i u) L ( ) + 1 η 4 i u + 8 η i u. (7) Tis gives 3 η 4 i u f L () (η i u) L ( ) + 8 η i u. (8) To proceed furter, we need to study te two terms 1 8 (η i u) L ( ) 1 8 (η i u) L ( ). We ave (η i u) L ( ) Were we ave used te fact tat η η. 8 η i u. We ave η i u (sup η ) and 8 η i u. ( (η )) i u L + η i u L (sup (η ) ) i u L + η i u L. (9) i u = (sup η ) i u L. (30) Tus we ave 1 η i u f L () (sup (η ) ) i u L + 8(sup η ) i u L. (31) Te following lemma ten guarantees te existence of u and also gives te desired estimate. Lemma. Let i u u(x +e i) u(x), 0 (3)

4 4 Poisson Equation in Sobolev Spaces wit e i being te it unit vector of R n. Let and < dist(, ). Ten Proof. 1. If u L () and tere is K < suc tat ten u W 1, ( ) and. Conversely, if u W 1, ( ), ten i u L ( ) wit i u L ( ) K (33) xi u L ( ) K. (34) i u L ( ) xi u L ( ). (35) 1. We first sow tat i u converges as distributions in D ( ) to te distributional derivative of u. Ceck ( i u) ϕ = u ( i ϕ ) u( xi ϕ) (36) by Lebesgue s dominated convergence teorem. We ave ( xi u)(ϕ) = lim ( i u) ϕ i u L ( ) ϕ L K ϕ L, ϕ C 0 ( ). (37) Now recall tat C 0 ( ) is dense in L ( ), ( xi u) can be identified wit a bounded linear operator on L, wic means it can be identified wit a function in L ( ).. Since C is dense in W 1,, we only need to consider te case wen u C W 1,. In tis case we ave i u(x)= 1 xi u(x 1,, x i 1, x i + s, x i+1,, x n ) ds. (38) 0 Tis gives i u(x) 1 xi u(x 1,, x i 1, x i +s, x i+1,, x n ) ds (39) 0 due to Hölder s inequality. Now integrate over and excange te order of integration on te RHS we obtain te result. Wit te elp of tis lemma (part b) ) we ave 1 η i u f L () (sup (η ) ) xi u L + 8(sup η ) xi u L. (40) wic is a uniform bound on i u L ( ) η i u. (41) Now part a) of te lemma yields xi u L ( ) and also te desired estimate. Wen f as better regularity, we can differentiate te equation first and obtain te following interior regularity result. Teorem 4. Let u W 1, () be a weak solution of u = f. If f W k, (), ten u W k+, ( ) for any, and Here te constant depends on d,, dist(, ). Boundary regularity.. Riesz representation teorem. u W k+, ( ) C ( u L () + f W k, ()). (4)

5 OcMountain Dayligt Time. 6, We consider te Poisson equation wit Diriclet boundary condition: u = f in ; u= g on (43) were g can be extended to a function on te wole. Our purpose is to establis te following result: Teorem 5. Let u be a weak solution wit u g W 0 1, (). If f W k, (), g W k+, (), and be of class C k+, ten and we ave te estimate Te constant C depends on. Proof. We only give an outline ere. u W k+, (), (44) u W k+, () C ( f W k, () + g W k+, ()). (45) 1. First note tat since g W k+, (), we can replace u by u g and reduce te problem to. We first establis W 1, bound: u= f, u W 0 1, (). (46) u W 1, C ( g W 1,+ f L ). (47) To see tis, use v =u g as te test function. We obtain u (u g) = f (u g) (48) terefore u u g + f (u g) 1 4 u + g + 1 ε f +ε u g. (49) Apply Poincaré s inequality to te last term and coosing ε to be small enoug, we obtain te desired estimate. 3. For any, we can estimate xix j u C ( u + f ) C ( g W 1, + f L ). Terefore it suffices to establis te desired estimate in a neigborood of te bondary. 4. We illustrate te basic idea by assuming part of te boundary is in x n =0. We try to sow te W, bound for u in a small alf-ball B R + B R {x n >0}. Note tat once tis is done, te boundary, wic is compact, can be covered by finitely many suc balls. First note tat xi u is well defined in B R + and belongs to L (B R + ). Now let η be a cut-off function in C 0 (B R ). For all j n, j ± u is well-defined and we can use te test function j (η j u) as we did wen proving te interior regularity, and obtain te desired bound for all xi x j u except xn x n u. Now notice tat te equation implies n 1 xn x n u = f i=1 and terefore tis term enjoys te same bound as oter double derivatives. xi x i u (50) 5. For general, we need to first cover by small balls, and ten do a cange of variable on eac of te balls to straigten tat part of te boundary. After doing tis, owever, te equation does not ave te simple form u= f (51) anymore and proving te estimate becomes as difficult as proving similar estimates for te general case. Remark 6. It turns out tat wen te boundary is smoot, one can actually extend te regularity to.

6 6 Poisson Equation in Sobolev Spaces Teorem. Let R n be a bounded domain of class C, and let g C ( ), f C (). Ten te Diriclet problem possesses a unique solution u wic is C ( ). u= f in ; u= g on, (5) Te key to te proof is te embedding W k,p () C m ( ) for 0 m < k d p. L p Regularity. Teorem 7. Let 1< p<, f L p (), and let w be te Newton potential of f. Ten w W,p (), w = f almost everywere in, and w L p () C(n, p) f L p (). (53) Using tis teorem, we can obtain te following interior regularity result. Teorem 8. Let u W 1, () be a weak solution of u = f, f L p (), 1< p <. Ten u W,p ( ) for any, and Here C = C(n, p,, ). u W,p ( ) C ( u L p () + f L p ()). (54)

Convexity and Smoothness

Convexity and Smoothness Capter 4 Convexity and Smootness 4.1 Strict Convexity, Smootness, and Gateaux Differentiablity Definition 4.1.1. Let X be a Banac space wit a norm denoted by. A map f : X \{0} X \{0}, f f x is called a

More information

The Dirichlet s P rinciple. In this lecture we discuss an alternative formulation of the Dirichlet problem for the Laplace equation:

The Dirichlet s P rinciple. In this lecture we discuss an alternative formulation of the Dirichlet problem for the Laplace equation: Oct. 1 The Dirichlet s P rinciple In this lecture we discuss an alternative formulation of the Dirichlet problem for the Laplace equation: 1. Dirichlet s Principle. u = in, u = g on. ( 1 ) If we multiply

More information

Math Spring 2013 Solutions to Assignment # 3 Completion Date: Wednesday May 15, (1/z) 2 (1/z 1) 2 = lim

Math Spring 2013 Solutions to Assignment # 3 Completion Date: Wednesday May 15, (1/z) 2 (1/z 1) 2 = lim Mat 311 - Spring 013 Solutions to Assignment # 3 Completion Date: Wednesday May 15, 013 Question 1. [p 56, #10 (a)] 4z Use te teorem of Sec. 17 to sow tat z (z 1) = 4. We ave z 4z (z 1) = z 0 4 (1/z) (1/z

More information

Order of Accuracy. ũ h u Ch p, (1)

Order of Accuracy. ũ h u Ch p, (1) Order of Accuracy 1 Terminology We consider a numerical approximation of an exact value u. Te approximation depends on a small parameter, wic can be for instance te grid size or time step in a numerical

More information

2.8 The Derivative as a Function

2.8 The Derivative as a Function .8 Te Derivative as a Function Typically, we can find te derivative of a function f at many points of its domain: Definition. Suppose tat f is a function wic is differentiable at every point of an open

More information

Convexity and Smoothness

Convexity and Smoothness Capter 4 Convexity and Smootness 4. Strict Convexity, Smootness, and Gateaux Di erentiablity Definition 4... Let X be a Banac space wit a norm denoted by k k. A map f : X \{0}!X \{0}, f 7! f x is called

More information

Differentiation in higher dimensions

Differentiation in higher dimensions Capter 2 Differentiation in iger dimensions 2.1 Te Total Derivative Recall tat if f : R R is a 1-variable function, and a R, we say tat f is differentiable at x = a if and only if te ratio f(a+) f(a) tends

More information

MATH1151 Calculus Test S1 v2a

MATH1151 Calculus Test S1 v2a MATH5 Calculus Test 8 S va January 8, 5 Tese solutions were written and typed up by Brendan Trin Please be etical wit tis resource It is for te use of MatSOC members, so do not repost it on oter forums

More information

MAT 145. Type of Calculator Used TI-89 Titanium 100 points Score 100 possible points

MAT 145. Type of Calculator Used TI-89 Titanium 100 points Score 100 possible points MAT 15 Test #2 Name Solution Guide Type of Calculator Used TI-89 Titanium 100 points Score 100 possible points Use te grap of a function sown ere as you respond to questions 1 to 8. 1. lim f (x) 0 2. lim

More information

NUMERICAL DIFFERENTIATION. James T. Smith San Francisco State University. In calculus classes, you compute derivatives algebraically: for example,

NUMERICAL DIFFERENTIATION. James T. Smith San Francisco State University. In calculus classes, you compute derivatives algebraically: for example, NUMERICAL DIFFERENTIATION James T Smit San Francisco State University In calculus classes, you compute derivatives algebraically: for example, f( x) = x + x f ( x) = x x Tis tecnique requires your knowing

More information

NOTES ON LINEAR SEMIGROUPS AND GRADIENT FLOWS

NOTES ON LINEAR SEMIGROUPS AND GRADIENT FLOWS NOTES ON LINEAR SEMIGROUPS AND GRADIENT FLOWS F. MAGGI Tese notes ave been written in occasion of te course Partial Differential Equations II eld by te autor at te University of Texas at Austin. Tey are

More information

Polynomial Interpolation

Polynomial Interpolation Capter 4 Polynomial Interpolation In tis capter, we consider te important problem of approximatinga function fx, wose values at a set of distinct points x, x, x,, x n are known, by a polynomial P x suc

More information

Continuity and Differentiability Worksheet

Continuity and Differentiability Worksheet Continuity and Differentiability Workseet (Be sure tat you can also do te grapical eercises from te tet- Tese were not included below! Typical problems are like problems -3, p. 6; -3, p. 7; 33-34, p. 7;

More information

A SHORT INTRODUCTION TO BANACH LATTICES AND

A SHORT INTRODUCTION TO BANACH LATTICES AND CHAPTER A SHORT INTRODUCTION TO BANACH LATTICES AND POSITIVE OPERATORS In tis capter we give a brief introduction to Banac lattices and positive operators. Most results of tis capter can be found, e.g.,

More information

CHAPTER 4. Elliptic PDEs

CHAPTER 4. Elliptic PDEs CHAPTER 4 Elliptic PDEs One of te main advantages of extending te class of solutions of a PDE from classical solutions wit continuous derivatives to weak solutions wit weak derivatives is tat it is easier

More information

The Derivative as a Function

The Derivative as a Function Section 2.2 Te Derivative as a Function 200 Kiryl Tsiscanka Te Derivative as a Function DEFINITION: Te derivative of a function f at a number a, denoted by f (a), is if tis limit exists. f (a) f(a + )

More information

A NON HOMOGENEOUS EXTRA TERM FOR THE LIMIT OF DIRICHLET PROBLEMS IN PERFORATED DOMAINS

A NON HOMOGENEOUS EXTRA TERM FOR THE LIMIT OF DIRICHLET PROBLEMS IN PERFORATED DOMAINS J. Casado Diaz & A. Garroni A NON HOMOGENEOUS EXTRA TERM FOR THE LIMIT OF DIRICHLET PROBLEMS IN PERFORATED DOMAINS J. CASADO DIAZ A. GARRONI Abstract: We study te asymptotic beaviour of Diriclet problems

More information

4.2 - Richardson Extrapolation

4.2 - Richardson Extrapolation . - Ricardson Extrapolation. Small-O Notation: Recall tat te big-o notation used to define te rate of convergence in Section.: Definition Let x n n converge to a number x. Suppose tat n n is a sequence

More information

MA119-A Applied Calculus for Business Fall Homework 4 Solutions Due 9/29/ :30AM

MA119-A Applied Calculus for Business Fall Homework 4 Solutions Due 9/29/ :30AM MA9-A Applied Calculus for Business 006 Fall Homework Solutions Due 9/9/006 0:0AM. #0 Find te it 5 0 + +.. #8 Find te it. #6 Find te it 5 0 + + = (0) 5 0 (0) + (0) + =.!! r + +. r s r + + = () + 0 () +

More information

Math 161 (33) - Final exam

Math 161 (33) - Final exam Name: Id #: Mat 161 (33) - Final exam Fall Quarter 2015 Wednesday December 9, 2015-10:30am to 12:30am Instructions: Prob. Points Score possible 1 25 2 25 3 25 4 25 TOTAL 75 (BEST 3) Read eac problem carefully.

More information

Gradient Descent etc.

Gradient Descent etc. 1 Gradient Descent etc EE 13: Networked estimation and control Prof Kan) I DERIVATIVE Consider f : R R x fx) Te derivative is defined as d fx) = lim dx fx + ) fx) Te cain rule states tat if d d f gx) )

More information

How to Find the Derivative of a Function: Calculus 1

How to Find the Derivative of a Function: Calculus 1 Introduction How to Find te Derivative of a Function: Calculus 1 Calculus is not an easy matematics course Te fact tat you ave enrolled in suc a difficult subject indicates tat you are interested in te

More information

Continuity and Differentiability of the Trigonometric Functions

Continuity and Differentiability of the Trigonometric Functions [Te basis for te following work will be te definition of te trigonometric functions as ratios of te sides of a triangle inscribed in a circle; in particular, te sine of an angle will be defined to be te

More information

MATH1131/1141 Calculus Test S1 v8a

MATH1131/1141 Calculus Test S1 v8a MATH/ Calculus Test 8 S v8a October, 7 Tese solutions were written by Joann Blanco, typed by Brendan Trin and edited by Mattew Yan and Henderson Ko Please be etical wit tis resource It is for te use of

More information

REVIEW LAB ANSWER KEY

REVIEW LAB ANSWER KEY REVIEW LAB ANSWER KEY. Witout using SN, find te derivative of eac of te following (you do not need to simplify your answers): a. f x 3x 3 5x x 6 f x 3 3x 5 x 0 b. g x 4 x x x notice te trick ere! x x g

More information

Numerical Analysis MTH603. dy dt = = (0) , y n+1. We obtain yn. Therefore. and. Copyright Virtual University of Pakistan 1

Numerical Analysis MTH603. dy dt = = (0) , y n+1. We obtain yn. Therefore. and. Copyright Virtual University of Pakistan 1 Numerical Analysis MTH60 PREDICTOR CORRECTOR METHOD Te metods presented so far are called single-step metods, were we ave seen tat te computation of y at t n+ tat is y n+ requires te knowledge of y n only.

More information

Volume 29, Issue 3. Existence of competitive equilibrium in economies with multi-member households

Volume 29, Issue 3. Existence of competitive equilibrium in economies with multi-member households Volume 29, Issue 3 Existence of competitive equilibrium in economies wit multi-member ouseolds Noriisa Sato Graduate Scool of Economics, Waseda University Abstract Tis paper focuses on te existence of

More information

Math 242: Principles of Analysis Fall 2016 Homework 7 Part B Solutions

Math 242: Principles of Analysis Fall 2016 Homework 7 Part B Solutions Mat 22: Principles of Analysis Fall 206 Homework 7 Part B Solutions. Sow tat f(x) = x 2 is not uniformly continuous on R. Solution. Te equation is equivalent to f(x) = 0 were f(x) = x 2 sin(x) 3. Since

More information

1 The concept of limits (p.217 p.229, p.242 p.249, p.255 p.256) 1.1 Limits Consider the function determined by the formula 3. x since at this point

1 The concept of limits (p.217 p.229, p.242 p.249, p.255 p.256) 1.1 Limits Consider the function determined by the formula 3. x since at this point MA00 Capter 6 Calculus and Basic Linear Algebra I Limits, Continuity and Differentiability Te concept of its (p.7 p.9, p.4 p.49, p.55 p.56). Limits Consider te function determined by te formula f Note

More information

232 Calculus and Structures

232 Calculus and Structures 3 Calculus and Structures CHAPTER 17 JUSTIFICATION OF THE AREA AND SLOPE METHODS FOR EVALUATING BEAMS Calculus and Structures 33 Copyrigt Capter 17 JUSTIFICATION OF THE AREA AND SLOPE METHODS 17.1 THE

More information

A variational approach to a quasi-static droplet model

A variational approach to a quasi-static droplet model A variational approac to a quasi-static droplet model Natalie Grunewald and Inwon Kim Abstract We consider a quasi-static droplet motion based on contact angle dynamics on a planar surface. We derive a

More information

Polynomial Interpolation

Polynomial Interpolation Capter 4 Polynomial Interpolation In tis capter, we consider te important problem of approximating a function f(x, wose values at a set of distinct points x, x, x 2,,x n are known, by a polynomial P (x

More information

Math 212-Lecture 9. For a single-variable function z = f(x), the derivative is f (x) = lim h 0

Math 212-Lecture 9. For a single-variable function z = f(x), the derivative is f (x) = lim h 0 3.4: Partial Derivatives Definition Mat 22-Lecture 9 For a single-variable function z = f(x), te derivative is f (x) = lim 0 f(x+) f(x). For a function z = f(x, y) of two variables, to define te derivatives,

More information

HOMEWORK HELP 2 FOR MATH 151

HOMEWORK HELP 2 FOR MATH 151 HOMEWORK HELP 2 FOR MATH 151 Here we go; te second round of omework elp. If tere are oters you would like to see, let me know! 2.4, 43 and 44 At wat points are te functions f(x) and g(x) = xf(x)continuous,

More information

A Finite Element Primer

A Finite Element Primer A Finite Element Primer David J. Silvester Scool of Matematics, University of Mancester d.silvester@mancester.ac.uk. Version.3 updated 4 October Contents A Model Diffusion Problem.................... x.

More information

Section 2.1 The Definition of the Derivative. We are interested in finding the slope of the tangent line at a specific point.

Section 2.1 The Definition of the Derivative. We are interested in finding the slope of the tangent line at a specific point. Popper 6: Review of skills: Find tis difference quotient. f ( x ) f ( x) if f ( x) x Answer coices given in audio on te video. Section.1 Te Definition of te Derivative We are interested in finding te slope

More information

Section 15.6 Directional Derivatives and the Gradient Vector

Section 15.6 Directional Derivatives and the Gradient Vector Section 15.6 Directional Derivatives and te Gradient Vector Finding rates of cange in different directions Recall tat wen we first started considering derivatives of functions of more tan one variable,

More information

Introduction to Derivatives

Introduction to Derivatives Introduction to Derivatives 5-Minute Review: Instantaneous Rates and Tangent Slope Recall te analogy tat we developed earlier First we saw tat te secant slope of te line troug te two points (a, f (a))

More information

The derivative function

The derivative function Roberto s Notes on Differential Calculus Capter : Definition of derivative Section Te derivative function Wat you need to know already: f is at a point on its grap and ow to compute it. Wat te derivative

More information

1 Calculus. 1.1 Gradients and the Derivative. Q f(x+h) f(x)

1 Calculus. 1.1 Gradients and the Derivative. Q f(x+h) f(x) Calculus. Gradients and te Derivative Q f(x+) δy P T δx R f(x) 0 x x+ Let P (x, f(x)) and Q(x+, f(x+)) denote two points on te curve of te function y = f(x) and let R denote te point of intersection of

More information

Subdifferentials of convex functions

Subdifferentials of convex functions Subdifferentials of convex functions Jordan Bell jordan.bell@gmail.com Department of Matematics, University of Toronto April 21, 2014 Wenever we speak about a vector space in tis note we mean a vector

More information

Semigroups of Operators

Semigroups of Operators Lecture 11 Semigroups of Operators In tis Lecture we gater a few notions on one-parameter semigroups of linear operators, confining to te essential tools tat are needed in te sequel. As usual, X is a real

More information

Click here to see an animation of the derivative

Click here to see an animation of the derivative Differentiation Massoud Malek Derivative Te concept of derivative is at te core of Calculus; It is a very powerful tool for understanding te beavior of matematical functions. It allows us to optimize functions,

More information

Lecture XVII. Abstract We introduce the concept of directional derivative of a scalar function and discuss its relation with the gradient operator.

Lecture XVII. Abstract We introduce the concept of directional derivative of a scalar function and discuss its relation with the gradient operator. Lecture XVII Abstract We introduce te concept of directional derivative of a scalar function and discuss its relation wit te gradient operator. Directional derivative and gradient Te directional derivative

More information

Precalculus Test 2 Practice Questions Page 1. Note: You can expect other types of questions on the test than the ones presented here!

Precalculus Test 2 Practice Questions Page 1. Note: You can expect other types of questions on the test than the ones presented here! Precalculus Test 2 Practice Questions Page Note: You can expect oter types of questions on te test tan te ones presented ere! Questions Example. Find te vertex of te quadratic f(x) = 4x 2 x. Example 2.

More information

Strongly continuous semigroups

Strongly continuous semigroups Capter 2 Strongly continuous semigroups Te main application of te teory developed in tis capter is related to PDE systems. Tese systems can provide te strong continuity properties only. 2.1 Closed operators

More information

LIMITS AND DERIVATIVES CONDITIONS FOR THE EXISTENCE OF A LIMIT

LIMITS AND DERIVATIVES CONDITIONS FOR THE EXISTENCE OF A LIMIT LIMITS AND DERIVATIVES Te limit of a function is defined as te value of y tat te curve approaces, as x approaces a particular value. Te limit of f (x) as x approaces a is written as f (x) approaces, as

More information

On convergence of the immersed boundary method for elliptic interface problems

On convergence of the immersed boundary method for elliptic interface problems On convergence of te immersed boundary metod for elliptic interface problems Zilin Li January 26, 2012 Abstract Peskin s Immersed Boundary (IB) metod is one of te most popular numerical metods for many

More information

arxiv: v1 [math.na] 20 Nov 2018

arxiv: v1 [math.na] 20 Nov 2018 An HDG Metod for Tangential Boundary Control of Stokes Equations I: Hig Regularity Wei Gong Weiwei Hu Mariano Mateos Jon R. Singler Yangwen Zang arxiv:1811.08522v1 [mat.na] 20 Nov 2018 November 22, 2018

More information

Smoothed projections in finite element exterior calculus

Smoothed projections in finite element exterior calculus Smooted projections in finite element exterior calculus Ragnar Winter CMA, University of Oslo Norway based on joint work wit: Douglas N. Arnold, Minnesota, Ricard S. Falk, Rutgers, and Snorre H. Cristiansen,

More information

Andrea Braides, Anneliese Defranceschi and Enrico Vitali. Introduction

Andrea Braides, Anneliese Defranceschi and Enrico Vitali. Introduction HOMOGENIZATION OF FREE DISCONTINUITY PROBLEMS Andrea Braides, Anneliese Defrancesci and Enrico Vitali Introduction Following Griffit s teory, yperelastic brittle media subject to fracture can be modeled

More information

Weierstraß-Institut. im Forschungsverbund Berlin e.v. Preprint ISSN

Weierstraß-Institut. im Forschungsverbund Berlin e.v. Preprint ISSN Weierstraß-Institut für Angewandte Analysis und Stocastik im Forscungsverbund Berlin e.v. Preprint ISSN 0946 8633 Stability of infinite dimensional control problems wit pointwise state constraints Micael

More information

Chapter 1. Density Estimation

Chapter 1. Density Estimation Capter 1 Density Estimation Let X 1, X,..., X n be observations from a density f X x. Te aim is to use only tis data to obtain an estimate ˆf X x of f X x. Properties of f f X x x, Parametric metods f

More information

(4.2) -Richardson Extrapolation

(4.2) -Richardson Extrapolation (.) -Ricardson Extrapolation. Small-O Notation: Recall tat te big-o notation used to define te rate of convergence in Section.: Suppose tat lim G 0 and lim F L. Te function F is said to converge to L as

More information

Solution. Solution. f (x) = (cos x)2 cos(2x) 2 sin(2x) 2 cos x ( sin x) (cos x) 4. f (π/4) = ( 2/2) ( 2/2) ( 2/2) ( 2/2) 4.

Solution. Solution. f (x) = (cos x)2 cos(2x) 2 sin(2x) 2 cos x ( sin x) (cos x) 4. f (π/4) = ( 2/2) ( 2/2) ( 2/2) ( 2/2) 4. December 09, 20 Calculus PracticeTest s Name: (4 points) Find te absolute extrema of f(x) = x 3 0 on te interval [0, 4] Te derivative of f(x) is f (x) = 3x 2, wic is zero only at x = 0 Tus we only need

More information

Function Composition and Chain Rules

Function Composition and Chain Rules Function Composition and s James K. Peterson Department of Biological Sciences and Department of Matematical Sciences Clemson University Marc 8, 2017 Outline 1 Function Composition and Continuity 2 Function

More information

Practice Problem Solutions: Exam 1

Practice Problem Solutions: Exam 1 Practice Problem Solutions: Exam 1 1. (a) Algebraic Solution: Te largest term in te numerator is 3x 2, wile te largest term in te denominator is 5x 2 3x 2 + 5. Tus lim x 5x 2 2x 3x 2 x 5x 2 = 3 5 Numerical

More information

Mass Lumping for Constant Density Acoustics

Mass Lumping for Constant Density Acoustics Lumping 1 Mass Lumping for Constant Density Acoustics William W. Symes ABSTRACT Mass lumping provides an avenue for efficient time-stepping of time-dependent problems wit conforming finite element spatial

More information

1 Lecture 13: The derivative as a function.

1 Lecture 13: The derivative as a function. 1 Lecture 13: Te erivative as a function. 1.1 Outline Definition of te erivative as a function. efinitions of ifferentiability. Power rule, erivative te exponential function Derivative of a sum an a multiple

More information

Numerical Differentiation

Numerical Differentiation Numerical Differentiation Finite Difference Formulas for te first derivative (Using Taylor Expansion tecnique) (section 8.3.) Suppose tat f() = g() is a function of te variable, and tat as 0 te function

More information

An approximation method using approximate approximations

An approximation method using approximate approximations Applicable Analysis: An International Journal Vol. 00, No. 00, September 2005, 1 13 An approximation metod using approximate approximations FRANK MÜLLER and WERNER VARNHORN, University of Kassel, Germany,

More information

MATH745 Fall MATH745 Fall

MATH745 Fall MATH745 Fall MATH745 Fall 5 MATH745 Fall 5 INTRODUCTION WELCOME TO MATH 745 TOPICS IN NUMERICAL ANALYSIS Instructor: Dr Bartosz Protas Department of Matematics & Statistics Email: bprotas@mcmasterca Office HH 36, Ext

More information

2.11 That s So Derivative

2.11 That s So Derivative 2.11 Tat s So Derivative Introduction to Differential Calculus Just as one defines instantaneous velocity in terms of average velocity, we now define te instantaneous rate of cange of a function at a point

More information

MATH 173: Problem Set 5 Solutions

MATH 173: Problem Set 5 Solutions MATH 173: Problem Set 5 Solutions Problem 1. Let f L 1 and a. Te wole problem is a matter of cange of variables wit integrals. i Ff a ξ = e ix ξ f a xdx = e ix ξ fx adx = e ia+y ξ fydy = e ia ξ = e ia

More information

MANY scientific and engineering problems can be

MANY scientific and engineering problems can be A Domain Decomposition Metod using Elliptical Arc Artificial Boundary for Exterior Problems Yajun Cen, and Qikui Du Abstract In tis paper, a Diriclet-Neumann alternating metod using elliptical arc artificial

More information

Section 2.7 Derivatives and Rates of Change Part II Section 2.8 The Derivative as a Function. at the point a, to be. = at time t = a is

Section 2.7 Derivatives and Rates of Change Part II Section 2.8 The Derivative as a Function. at the point a, to be. = at time t = a is Mat 180 www.timetodare.com Section.7 Derivatives and Rates of Cange Part II Section.8 Te Derivative as a Function Derivatives ( ) In te previous section we defined te slope of te tangent to a curve wit

More information

3.4 Worksheet: Proof of the Chain Rule NAME

3.4 Worksheet: Proof of the Chain Rule NAME Mat 1170 3.4 Workseet: Proof of te Cain Rule NAME Te Cain Rule So far we are able to differentiate all types of functions. For example: polynomials, rational, root, and trigonometric functions. We are

More information

Exam 1 Solutions. x(x 2) (x + 1)(x 2) = x

Exam 1 Solutions. x(x 2) (x + 1)(x 2) = x Eam Solutions Question (0%) Consider f() = 2 2 2 2. (a) By calculating relevant its, determine te equations of all vertical asymptotes of te grap of f(). If tere are none, say so. f() = ( 2) ( + )( 2)

More information

Continuity. Example 1

Continuity. Example 1 Continuity MATH 1003 Calculus and Linear Algebra (Lecture 13.5) Maoseng Xiong Department of Matematics, HKUST A function f : (a, b) R is continuous at a point c (a, b) if 1. x c f (x) exists, 2. f (c)

More information

Solutions to the Multivariable Calculus and Linear Algebra problems on the Comprehensive Examination of January 31, 2014

Solutions to the Multivariable Calculus and Linear Algebra problems on the Comprehensive Examination of January 31, 2014 Solutions to te Multivariable Calculus and Linear Algebra problems on te Compreensive Examination of January 3, 24 Tere are 9 problems ( points eac, totaling 9 points) on tis portion of te examination.

More information

LEAST-SQUARES FINITE ELEMENT APPROXIMATIONS TO SOLUTIONS OF INTERFACE PROBLEMS

LEAST-SQUARES FINITE ELEMENT APPROXIMATIONS TO SOLUTIONS OF INTERFACE PROBLEMS SIAM J. NUMER. ANAL. c 998 Society for Industrial Applied Matematics Vol. 35, No., pp. 393 405, February 998 00 LEAST-SQUARES FINITE ELEMENT APPROXIMATIONS TO SOLUTIONS OF INTERFACE PROBLEMS YANZHAO CAO

More information

BOUNDARY REGULARITY FOR SOLUTIONS TO THE LINEARIZED MONGE-AMPÈRE EQUATIONS

BOUNDARY REGULARITY FOR SOLUTIONS TO THE LINEARIZED MONGE-AMPÈRE EQUATIONS BOUNDARY REGULARITY FOR SOLUTIONS TO THE LINEARIZED MONGE-AMPÈRE EQUATIONS N. Q. LE AND O. SAVIN Abstract. We obtain boundary Hölder gradient estimates and regularity for solutions to te linearized Monge-Ampère

More information

arxiv:math/ v1 [math.ca] 1 Oct 2003

arxiv:math/ v1 [math.ca] 1 Oct 2003 arxiv:mat/0310017v1 [mat.ca] 1 Oct 2003 Cange of Variable for Multi-dimensional Integral 4 Marc 2003 Isidore Fleiscer Abstract Te cange of variable teorem is proved under te sole ypotesis of differentiability

More information

1. Questions (a) through (e) refer to the graph of the function f given below. (A) 0 (B) 1 (C) 2 (D) 4 (E) does not exist

1. Questions (a) through (e) refer to the graph of the function f given below. (A) 0 (B) 1 (C) 2 (D) 4 (E) does not exist Mat 1120 Calculus Test 2. October 18, 2001 Your name Te multiple coice problems count 4 points eac. In te multiple coice section, circle te correct coice (or coices). You must sow your work on te oter

More information

A Hybrid Mixed Discontinuous Galerkin Finite Element Method for Convection-Diffusion Problems

A Hybrid Mixed Discontinuous Galerkin Finite Element Method for Convection-Diffusion Problems A Hybrid Mixed Discontinuous Galerkin Finite Element Metod for Convection-Diffusion Problems Herbert Egger Joacim Scöberl We propose and analyse a new finite element metod for convection diffusion problems

More information

2.3 Product and Quotient Rules

2.3 Product and Quotient Rules .3. PRODUCT AND QUOTIENT RULES 75.3 Product and Quotient Rules.3.1 Product rule Suppose tat f and g are two di erentiable functions. Ten ( g (x)) 0 = f 0 (x) g (x) + g 0 (x) See.3.5 on page 77 for a proof.

More information

OSCILLATION OF SOLUTIONS TO NON-LINEAR DIFFERENCE EQUATIONS WITH SEVERAL ADVANCED ARGUMENTS. Sandra Pinelas and Julio G. Dix

OSCILLATION OF SOLUTIONS TO NON-LINEAR DIFFERENCE EQUATIONS WITH SEVERAL ADVANCED ARGUMENTS. Sandra Pinelas and Julio G. Dix Opuscula Mat. 37, no. 6 (2017), 887 898 ttp://dx.doi.org/10.7494/opmat.2017.37.6.887 Opuscula Matematica OSCILLATION OF SOLUTIONS TO NON-LINEAR DIFFERENCE EQUATIONS WITH SEVERAL ADVANCED ARGUMENTS Sandra

More information

Combining functions: algebraic methods

Combining functions: algebraic methods Combining functions: algebraic metods Functions can be added, subtracted, multiplied, divided, and raised to a power, just like numbers or algebra expressions. If f(x) = x 2 and g(x) = x + 2, clearly f(x)

More information

1. State whether the function is an exponential growth or exponential decay, and describe its end behaviour using limits.

1. State whether the function is an exponential growth or exponential decay, and describe its end behaviour using limits. Questions 1. State weter te function is an exponential growt or exponential decay, and describe its end beaviour using its. (a) f(x) = 3 2x (b) f(x) = 0.5 x (c) f(x) = e (d) f(x) = ( ) x 1 4 2. Matc te

More information

MVT and Rolle s Theorem

MVT and Rolle s Theorem AP Calculus CHAPTER 4 WORKSHEET APPLICATIONS OF DIFFERENTIATION MVT and Rolle s Teorem Name Seat # Date UNLESS INDICATED, DO NOT USE YOUR CALCULATOR FOR ANY OF THESE QUESTIONS In problems 1 and, state

More information

SFU UBC UNBC Uvic Calculus Challenge Examination June 5, 2008, 12:00 15:00

SFU UBC UNBC Uvic Calculus Challenge Examination June 5, 2008, 12:00 15:00 SFU UBC UNBC Uvic Calculus Callenge Eamination June 5, 008, :00 5:00 Host: SIMON FRASER UNIVERSITY First Name: Last Name: Scool: Student signature INSTRUCTIONS Sow all your work Full marks are given only

More information

Overlapping domain decomposition methods for elliptic quasi-variational inequalities related to impulse control problem with mixed boundary conditions

Overlapping domain decomposition methods for elliptic quasi-variational inequalities related to impulse control problem with mixed boundary conditions Proc. Indian Acad. Sci. (Mat. Sci.) Vol. 121, No. 4, November 2011, pp. 481 493. c Indian Academy of Sciences Overlapping domain decomposition metods for elliptic quasi-variational inequalities related

More information

Convergence of Rothe s Method for Fully Nonlinear Parabolic Equations

Convergence of Rothe s Method for Fully Nonlinear Parabolic Equations Te Journal of Geometric Analysis Volume 15, Number 3, 2005 Convergence of Rote s Metod for Fully Nonlinear Parabolic Equations By Ivan Blank and Penelope Smit ABSTRACT. Convergence of Rote s metod for

More information

ERROR BOUNDS FOR FINITE-DIFFERENCE METHODS FOR RUDIN OSHER FATEMI IMAGE SMOOTHING

ERROR BOUNDS FOR FINITE-DIFFERENCE METHODS FOR RUDIN OSHER FATEMI IMAGE SMOOTHING ERROR BOUNDS FOR FINITE-DIFFERENCE METHODS FOR RUDIN OSHER FATEMI IMAGE SMOOTHING JINGYUE WANG AND BRADLEY J. LUCIER Abstract. We bound te difference between te solution to te continuous Rudin Oser Fatemi

More information

Finite Difference Method

Finite Difference Method Capter 8 Finite Difference Metod 81 2nd order linear pde in two variables General 2nd order linear pde in two variables is given in te following form: L[u] = Au xx +2Bu xy +Cu yy +Du x +Eu y +Fu = G According

More information

Consider a function f we ll specify which assumptions we need to make about it in a minute. Let us reformulate the integral. 1 f(x) dx.

Consider a function f we ll specify which assumptions we need to make about it in a minute. Let us reformulate the integral. 1 f(x) dx. Capter 2 Integrals as sums and derivatives as differences We now switc to te simplest metods for integrating or differentiating a function from its function samples. A careful study of Taylor expansions

More information

10 Derivatives ( )

10 Derivatives ( ) Instructor: Micael Medvinsky 0 Derivatives (.6-.8) Te tangent line to te curve yf() at te point (a,f(a)) is te line l m + b troug tis point wit slope Alternatively one can epress te slope as f f a m lim

More information

. Compute the following limits.

. Compute the following limits. Today: Tangent Lines and te Derivative at a Point Warmup:. Let f(x) =x. Compute te following limits. f( + ) f() (a) lim f( +) f( ) (b) lim. Let g(x) = x. Compute te following limits. g(3 + ) g(3) (a) lim

More information

Analytic Functions. Differentiable Functions of a Complex Variable

Analytic Functions. Differentiable Functions of a Complex Variable Analytic Functions Differentiable Functions of a Complex Variable In tis capter, we sall generalize te ideas for polynomials power series of a complex variable we developed in te previous capter to general

More information

1. Consider the trigonometric function f(t) whose graph is shown below. Write down a possible formula for f(t).

1. Consider the trigonometric function f(t) whose graph is shown below. Write down a possible formula for f(t). . Consider te trigonometric function f(t) wose grap is sown below. Write down a possible formula for f(t). Tis function appears to be an odd, periodic function tat as been sifted upwards, so we will use

More information

NUMERICAL DIFFERENTIATION

NUMERICAL DIFFERENTIATION NUMERICAL IFFERENTIATION FIRST ERIVATIVES Te simplest difference formulas are based on using a straigt line to interpolate te given data; tey use two data pints to estimate te derivative. We assume tat

More information

Logarithmic functions

Logarithmic functions Roberto s Notes on Differential Calculus Capter 5: Derivatives of transcendental functions Section Derivatives of Logaritmic functions Wat ou need to know alread: Definition of derivative and all basic

More information

Chapter 5 FINITE DIFFERENCE METHOD (FDM)

Chapter 5 FINITE DIFFERENCE METHOD (FDM) MEE7 Computer Modeling Tecniques in Engineering Capter 5 FINITE DIFFERENCE METHOD (FDM) 5. Introduction to FDM Te finite difference tecniques are based upon approximations wic permit replacing differential

More information

THE IMPLICIT FUNCTION THEOREM

THE IMPLICIT FUNCTION THEOREM THE IMPLICIT FUNCTION THEOREM ALEXANDRU ALEMAN 1. Motivation and statement We want to understand a general situation wic occurs in almost any area wic uses matematics. Suppose we are given number of equations

More information

MIXED DISCONTINUOUS GALERKIN APPROXIMATION OF THE MAXWELL OPERATOR. SIAM J. Numer. Anal., Vol. 42 (2004), pp

MIXED DISCONTINUOUS GALERKIN APPROXIMATION OF THE MAXWELL OPERATOR. SIAM J. Numer. Anal., Vol. 42 (2004), pp MIXED DISCONTINUOUS GALERIN APPROXIMATION OF THE MAXWELL OPERATOR PAUL HOUSTON, ILARIA PERUGIA, AND DOMINI SCHÖTZAU SIAM J. Numer. Anal., Vol. 4 (004), pp. 434 459 Abstract. We introduce and analyze a

More information

LECTURE 14 NUMERICAL INTEGRATION. Find

LECTURE 14 NUMERICAL INTEGRATION. Find LECTURE 14 NUMERCAL NTEGRATON Find b a fxdx or b a vx ux fx ydy dx Often integration is required. However te form of fx may be suc tat analytical integration would be very difficult or impossible. Use

More information

MA455 Manifolds Solutions 1 May 2008

MA455 Manifolds Solutions 1 May 2008 MA455 Manifolds Solutions 1 May 2008 1. (i) Given real numbers a < b, find a diffeomorpism (a, b) R. Solution: For example first map (a, b) to (0, π/2) and ten map (0, π/2) diffeomorpically to R using

More information

2.1 THE DEFINITION OF DERIVATIVE

2.1 THE DEFINITION OF DERIVATIVE 2.1 Te Derivative Contemporary Calculus 2.1 THE DEFINITION OF DERIVATIVE 1 Te grapical idea of a slope of a tangent line is very useful, but for some uses we need a more algebraic definition of te derivative

More information

Integral Calculus, dealing with areas and volumes, and approximate areas under and between curves.

Integral Calculus, dealing with areas and volumes, and approximate areas under and between curves. Calculus can be divided into two ke areas: Differential Calculus dealing wit its, rates of cange, tangents and normals to curves, curve sketcing, and applications to maima and minima problems Integral

More information

INTRODUCTION TO CALCULUS LIMITS

INTRODUCTION TO CALCULUS LIMITS Calculus can be divided into two ke areas: INTRODUCTION TO CALCULUS Differential Calculus dealing wit its, rates of cange, tangents and normals to curves, curve sketcing, and applications to maima and

More information